Abstract B023: Personalized phenotypic ex vivo drug sensitivity platform identifies frequent HDAC inhibitor-based combination sensitivities in T-cell lymphomas
Authors: Jasmine Ya Hwee Goh, Sanjay De Mel, Masturah Rashid, Anand Jeyasekharan, Edward Kai-Hua Chow
Journal: Cancer Research (2022)

Abstract T cell lymphomas (TCLs) are a heterogenous collection of non-Hodgkin lymphomas which have significantly higher incidences in Asian countries and are characterized by poor survival outcomes. Although histone deactylase (HDAC) inhibitors, such as romidepsin, have been approved for TCL, a major hurdle for effective implementation of these drugs include low overall responses to monotherapy treatments and a lack of clear biomarkers to define which patients amongst the heterogenous TCL population would benefit from specific drugs. As such, HDAC inhibitors are not widely implemented and improving therapeutic treatment for TCLs, particularly amongst Asian patients, is still an unmet clinical need. We have developed an experimental-analytics hybrid platform, quadratic phenotypic optimization platform (QPOP), that maximizes use of small focused datasets to quickly identify all interactions within a set of drugs and rank all possible drug combinations towards a desired biological effect output. When applied towards primary patient samples, QPOP was able to rank and compare all possible drug combinations (531,441 total possible combinations) in a 12-drug, 3-dose drug search set from 155 test combinations. Early application of QPOP towards TCL successfully guided treatment of bortezomib/panobinostat in a late-stage refractory/relapsed TCL case that resulted in durable complete response. Given the success of HDAC inhibitor-based drug combinations in refractory/relapsed TCL, we hypothesized that QPOP can be applied towards TCL to identify more effective HDAC inhibitor-based combinations for specific patients, as well as specific TCL subpopulations. As such, we applied QPOP towards a cohort of 28 TCL patients who had received ≥ 2 prior lines of treatment. QPOP analysis revealed that HDAC inhibitor-based drug combinations were the most frequently reoccurring top-ranked combinations for TCL. Similar to the early case study, HDAC inhibitor-based combinations with the proteasome inhibitor, bortezomib, were frequently identified as high-ranked combinations. Even more frequent, however, were combinations of romidepsin with the PI3K inhibitor, copanlisib, or romidepsin with ifosfamide. Treatment with QPOP-guided romidepsin-based drug combinations resulted in several notable responses, including a 22.11x improvement in progression free survival for one case of romidepsin/copanlisib over prior treatment. Romidepsin-based combination rankings between these the three most common combinations were often distinct and separate, suggesting different TCL subtypes likely benefit from distinct romidepsin-based combinations. Furthermore, romidepsin-based combination ranking was not directly correlated with single-drug romidepsin half-maximal inhibitor concentration (IC50). This suggests that ex vivo single-drug dose response analysis is not sufficient to identify romidepsin-based combination sensitivity and may benefit from combination therapy-focused platforms. This study provides the rationale for increased clinical study of HDAC-based drug combinations in TCL. Citation Format: Jasmine Ya Hwee Goh, Sanjay De Mel, Masturah Rashid, Anand Jeyasekharan, Edward Kai-Hua Chow. Personalized phenotypic ex vivo drug sensitivity platform identifies frequent HDAC inhibitor-based combination sensitivities in T-cell lymphomas. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr B023.